Modelling sea lice control by lumpfish on Atlantic salmon farms : interactions with mate limitation, temperature and treatment rules

McEwan, Gregor F. and Groner, Maya L. and Cohen, Allegra A. B. and Imsland, Albert K. D. and Revie, Crawford W. (2019) Modelling sea lice control by lumpfish on Atlantic salmon farms : interactions with mate limitation, temperature and treatment rules. Diseases of Aquatic Organisms, 133 (1). pp. 69-82. ISSN 0177-5103 (https://doi.org/10.3354/dao03329)

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Abstract

Atlantic salmon farming is one of the largest aquaculture sectors in the world. A major impact on farm economics, fish welfare and, potentially, nearby wild salmonid populations, is the sea louse ectoparasite Lepeophtheirus salmonis. Sea louse infestations are most often controlled through application of chemicals, but in most farming regions, sea lice have evolved resistance to the small set of available chemicals. Therefore, alternative treatment methodologies are becoming more widely used. One increasingly common alternative treatment involves the co-culture of farmed salmon with cleaner fish, which prey on sea lice. However, despite their wide use, little is understood about the situations in which cleaner fish are most effective. For example, previous work suggests that a low parasite density results in sea lice finding it difficult to acquire mates, reducing fecundity and population growth. Other work suggests that environmental conditions such as temperature and external sea louse pressure have substantial impact on this mate limitation threshold and may even remove the effect entirely. We used an Agent-Based Model (ABM) to simulate cleaner fish on a salmon farm to explore interactions between sea louse mating behaviour, cleaner fish feeding rate, temperature and external sea louse pressure. We found that sea louse mating has a substantial effect on sea louse infestations under a variety of environmental conditions. Our results suggest that cleaner fish can control sea louse infestations most effectively by maintaining the population below critical density thresholds.

  • Item type:Article
    ID code:68921
    Dates:
    Date
    Event
    21 February 2019
    Published
    21 February 2019
    Published Online
    4 December 2018
    Accepted
    5 July 2018
    Submitted
    Subjects:Science
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:18 Jul 2019 14:58
    Last modified:16 Apr 2024 00:25
    URI:https://strathprints.strath.ac.uk/id/eprint/68921
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